Description
This book gathers notes from lectures given during a three-week summer school on the fundamentals and the most recent developments of geophysical data assimilation. Eric Blayo is a Professor in applied mathematics at the University of Grenoble. He is leading a research team working on the development of mathematical and numerical methods for environmental applications.; Marc Bocquet is a Professor and Senior Researcher at the environment research centre (CEREA), a joint laboratory of Ecole des Ponts ParisTech and EDF R&D. He is working in the field of data assimilation in geosciences.; Emmanuel Cosme obtained his PhD in Earth Sciences at the University of Grenoble in 2002. Thereafter, he worked during 2 years on data assimilation for air quality in Canada, and moved back to Grenoble as an Associate Professor, to specialise in ocean data assimilation.; Leticia F. Cugliandolo: Laboratoire de Physique Theorique et Hautes Energies Universite Pierre et Marie Curie – Paris 6, Paris, France. PART I – KEY LECTURES; 1 Olivier Talagrand: 4D-VAR: four dimensional variational assimilation; 2 Andrew Lorenc: Four-dimensional variational data assimilation; 3 Chris Snyder: Introduction to the Kalman filter; 4 Emmanuel Cosme: Smoothers; 5 Carla Cardinali: Observation influence diagnostic of a data assimilation system; 6 Carla Cardinali: Observation impact on the short range forecast; PART II – SPECIALIZED LECTURES; 7 Loik Berre: Background error covariances: estimation and specification; 8 Gerald Desroziers: Observation error specifications; 9 Olivier Talagrand: Errors. A posteriori diagnostics; 10 Peter Houtekamer: Error dynamics in ensemble Kalman filter systems: Localization; 11 Peter Houtekamer: Short-range error statistics in an ensemble Kalman filter; 12 Peter Houtekamer: Error dynamics in ensemble Kalman filter systems: System error; 13 Peter Jan Van Leeuwen: Particle filters for the geosciences; 14 Francois-Xavier Le Dimet, Igor Gejadze, and Victor Shutyaev: Second order methods for error propagation in variational data assimilation; 15 Laurent Hascoet: Adjoints by automatic differentiation; 16 Arthur Vidard: Assimilation of images; 17 Laurent Debreu, Emilie Neveu, Ehouarn Simon, and Francois-Xavier Le Dimet: Multigrid algorithms and local mesh refinement methods in the context of variational data assimilation; 18 Marc Bocquet, Lin Wu, Frederic Chevallier, and Mohammad Reza Koohkan: Selected topics in multiscale data assimilation; 19 Florence Rabier and Mike Fisher: Data assimilation in meteorology; 20 Marc Bocquet: An introduction to inverse modelling and parameter estimation for atmospheric and oceanic sciences; 21 Frederic Chevallier: Greenhouse gas fluxes inversion; 22 Hendrik Elbern, Elmar Friese, Lars Nieradzik, and Jorg Schwinger: Data assimilation in atmospheric chemistry and air quality; 23 Ichiro Fukumori: Combining models and data in large-scale oceanography: examples from the consortium for Estimating the Circulation and Climate of the Ocean (ECCO); 24 Javier Zavala-Garay, John Wilkin, and Julia Levin: Data assimilation in coastal oceanography: IS4DVAR in the Regional Ocean Modeling System (ROMS); 25 Bertrand Bonan, Maelle Nodet, Olivier Ozenda, and Catherine Ritz: Data assimilation in glaciology
